Privacy Preserving Data Mining
Authors: Vaidya, Jaideep, Clifton, Christopher W., Zhu, Yu Michael
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- About this book
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Data mining has emerged as a significant technology for gaining knowledge from vast quantities of data. However, concerns are growing that use of this technology can violate individual privacy. These concerns have led to a backlash against the technology, for example, a "Data-Mining Moratorium Act" introduced in the U.S. Senate that would have banned all data-mining programs (including research and development) by the U.S. Department of Defense.
Privacy Preserving Data Mining provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. This book demonstrates how these approaches can achieve data mining, while operating within legal and commercial restrictions that forbid release of data. Furthermore, this research crystallizes much of the underlying foundation, and inspires further research in the area.
Privacy Preserving Data Mining is designed for a professional audience composed of practitioners and researchers in industry. This volume is also suitable for graduate-level students in computer science.
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Privacy Preserving Data Mining
- Authors
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- Jaideep Vaidya
- Christopher W. Clifton
- Yu Michael Zhu
- Series Title
- Advances in Information Security
- Series Volume
- 19
- Copyright
- 2006
- Publisher
- Springer US
- Copyright Holder
- Springer-Verlag US
- eBook ISBN
- 978-0-387-29489-6
- DOI
- 10.1007/978-0-387-29489-6
- Hardcover ISBN
- 978-0-387-25886-7
- Softcover ISBN
- 978-1-4419-3847-3
- Series ISSN
- 1568-2633
- Edition Number
- 1
- Number of Pages
- X, 122
- Number of Illustrations and Tables
- 20 b/w illustrations
- Topics
